Depression and Body Mass Index, a U-shaped association.
A community based study exploring a non linear association between
BMI and depression.
Authors:
Leonore M de Wit*¹, Annemieke van Straten¹, Marieke van Herten2, Brenda WJH
Penninx3, Pim Cuijpers¹.
1
Department of Clinical Psychology and EMGO-Institute, VU University Amsterdam,
van der Boechorststraat 1, 1081 BT, Amsterdam, the Netherlands. 2 Division of
Social and Spatial Statistics, Statistics Netherlands, Heerlen, the Netherlands.
3
Department of Psychiatry and EMGO-Institute, VU University Medical Centre,
Amsterdam, the Netherlands.
*Correspondence: Drs. L.M. de Wit, Vrije Universiteit Amsterdam, van der
Boechorststraat 1, 1081 BT, Amsterdam, the Netherlands.
Tel. 0031(0)205988968
Fax. 0031(0)205988758
E-mail. [email protected]
Abstract
Background: Results of studies concerning the association between obesity and
depression are conflicting. Some find a positive association, some a negative
association and some find no association at all. Most studies, however, examine a
linear association between Body Mass Index (BMI) and depression. The present
study investigates if a nonlinear (U-shaped) trend is preferable over a linear trend to
describe the relationship between BMI and depression, which means that both
underweight and obesity are associated with depression.
Methods: We investigated the existence of such a U-curve in a sample of 43,534
individuals, aged between 18-90 years, who participated in a cross-sectional study
(Permanent Research of Life Situation) of physical and mental health in the general
population of the Netherlands. We calculated linear and nonlinear (quadratic)
ANOVA with polynomial contrast and curve fit regression statistics to investigate
whether there was a U-shaped trend in the association between BMI and depression.
Results: We find a very significant U-shaped association between BMI categories
(underweight, normal, overweight and obesity) and depression (p≤ 0.001). There is a
trend indicating a significant difference in the association between males and females
(p= 0.05). We find a very significant U-shaped (quadratic) association between BMI
(BMI2) and depression (p ≤ 0.001), continuous BMI is not linearly associated with
depression (p= 0.514).
Conclusion: The results of this study give evidence for a significant U-shaped trend
in the association between BMI and depression.
2
Background
In recent decades, the association between obesity and depression has been
examined in a considerable number of studies [1, 2]. Both conditions are associated
with increased risk of disability, reduced quality of life, increased mortality and co
morbid conditions such as cancer, diabetes and coronary heart disease. The
prevalence of both obesity and depression is very high, and both are associated with
an enormous individual burden and huge economic costs [3].
Weight gain is for the most part influenced by decreased physical activity and
increased intake of calorie-dense food. The development of obesity depends on
genetic, metabolic and environmental factors [1, 4]. Depression is caused by a
combination of biological, psychological and social factors, and most researchers
support vulnerability-stress models. In these models the development of a depressive
disorder is triggered when a vulnerable (psychological and/or biological) individual
experiences a life event or severe stress [5-9].
The exact underlying mechanism for the relationship between depression and
obesity is not clear. Depression may cause obesity, for example through changing
eating patterns or reduced physical activity [16-18]. But it is also possible that obesity
may cause depression, for example through the negative body image which is the
result of obesity [19]. Depression and obesity may also be caused by a third
underlying factor. Socio demographic factors may moderate the association between
depression and Body Mass Index (BMI, weight in kilograms divided by height in
meters squared) [20].
Before causal pathways can be explored further, it is necessary to establish the
exact pattern in which depression and obesity are associated with each other. Until
now, three hypotheses have been suggested: a positive association between
3
depression and obesity (higher depression is associated with more obesity) [10-12],
a negative association (higher depression is associated with lower obesity), and no
association [21, 13, 15].
From a psychiatric point of view, however, it could be expected that both
overweight and underweight are associated with depression. According to the DSMIV [22], in which the diagnoses of mental disorders are described, eating problems
(eating too much or eating too little) and changed physical activity (increased or
decreased) both constitute core symptoms of a major depressive disorder. Based on
this, one would not expect a linear association between depression and obesity, but
a U-curved association in which people with underweight and overweight report more
depressive symptoms, compared to people with a normal weight. Although this
seems an obvious association, we could find only few studies in which the existence
of such a U-curve was tested [23, 24]. The first study [23] only found a U-curve for
the unadjusted data. The second study [24] found a U-curve when comparing normal
weight, overweight and obese category, but they did not include an underweight
category. Therefore, we decided to examine in a large population based sample
whether we could find evidence for the existence of such a U-curve.
4
Methods
Study population
To monitor the physical and mental health of the general population of the
Netherlands, a survey was carried out by the Statistics Netherlands (CBS). Details of
sampling and procedures have been reported elsewhere [25]. Each year a
representative sample of 10.000 individuals, was invited by letter for an interview.
The initial non-response rate varies each year between 35-40%. This cross-sectional
study used a sample of all respondents aged between 18 and 90 years, who
participated between the year 2001 and 2006. In total, 43,534 inhabitants of the
Netherlands participated in this time period. All participants were interviewed at home
by a trained interviewer. The interview consisted of a broad range of questionnaires
evaluating aspects that included BMI and psychological well-being using Computer
Assisted Personal Interviewing (CAPI). Of the total sample (43,534), 3,474 (10.3%)
were considered obese, 11,898 (35.3%) participants were overweight, 17,748
(52.6%) had a normal weight and a total of 605 (1.8%) had underweight, while 9,809
(22.5%) had missing values.
Measures
Body Mass Index (BMI) was calculated as weight (kg) divided by height in
meters squared (m²). Height and weight were self-reported. BMI was classified into
four categories: Underweight (BMI< 18.5 kg/m2), Normal weight (BMI 18.5-24.9
kg/m2), Overweight (BMI 25.0-29.9 kg/m2) and Obesity (BMI> 30.0 kg/m2) [26].
Depressive symptoms were rated using the Mental Health Inventory (MHI),
which is a 5 item subscale with 6 response categories each, of the Short Format-36
(SF-36), an extensive international standard for measuring common health status
5
[27]. The MHI measures psychological health, so we calculated inverse scores of the
MHI as an indication of depression symptoms and transformed them to a scale with a
range 0 to 100 points, higher scores indicate an elevated level of depressive
symptomatology. Socio demographic variables examined were: gender, age,
ethnicity and level of education. Table 1 gives a description of the variables used in
our analyses, and their association with BMI level.
Data Analysis
All the analyses were conducted with SPSS 12.0.1 for Windows (SPSS Inc.,
Chicago, Illinois, USA). First we tested whether there was a statistical association
between BMI and depressive symptoms and whether the observations of the socio
demographic variables were associated with BMI, using Pearson χ² test.
We investigated whether the association between BMI categories
(underweight, normal weight, overweight and obesity) and depression was U-shaped.
Therefore we conducted univariate linear and non linear ANOVA with polynomial
contrast. Besides linear trends, this method also examines quadratic (U-shaped)
trends [28]. The linear contrast compared the lowest with the highest BMI category
and the quadratic compares both middle with the highest and the lowest BMI
categories together [29].
We also conducted multivariate ANOVA with polynomial contrast for the BMI
categories and depression (underweight, normal weight, overweight and obesity),
controlling for socio-demographic variables (gender, age, ethnicity, year of
publication). Additionally, we tested whether the association between categorical BMI
and depression was different for males and females. To test this question we
6
included an interaction term for BMI and gender in our analysis (ANOVA with
polynomial contrast).
We investigated whether the association between continuous BMI and
depression was linear (BMI) or quadratic (U-shaped), using curve fit regression
statistics [30]. This method calculated linear and non linear regression statistics
including quadratic (U-shaped) trends. The method evaluates whether there is a
deviation from linearity and if this is indeed present, it examines whether a quadratic
trend is involved. Additionally, these analyses were repeated for the association
between continuous BMI and depression in the different age and gender subgroups.
7
Results
In the first set of analyses we tested whether there was an association
between BMI and depression. The results of Pearson χ² test showed a significant
cross-sectional association between BMI and depression (p≤ 0.001) Table 1 shows
the distribution of the socio demographic variables (gender, age, ethnicity, level of
education, year of the study) and their association with BMI. As expected, the χ²
analysis for depression and the socio demographic variables showed all significant
(p< 0.05) associations.
U-shaped association
Results of the polynomial trend analyses indicated a significant positive quadratic
effect between categorical BMI and depression (p≤ 0.001). After controlling for socio
demographic variables (gender, age, ethnicity, level of education), the positive
quadratic effect remained significant (p≤ 0.001) (Figure 1). Results of the interaction
test for gender, showed a trend indicating a possible difference in the association
between males and females (p= 0.05).
Furthermore we conducted confirmative analyses with the continuous
indicator of BMI, expecting quadratic association. Results showed a significant
quadratic association (β= 0.430, p≤ 0.001) and a non significant linear association
(β= -0.004, p= 0.514) between BMI and depression. Table 2 gives an overview of
quadratic regression statistics for quadratic association between BMI and
depression in the subgroups age and gender, which were all significant (p≤ 0.001).
8
Discussion and Conclusion
The goal of this study was to explore if there is a U-shaped trend in the
association between BMI and depression. In this community based sample of 43,534
participants we indeed found evidence of such a positive U-curve. Both BMI
categories and BMI continuous BMI are nonlinear (U-shaped) associated with
depression. We demonstrated that both obesity and underweight are associated with
an increased level of depression, even after controlling for various socio
demographic variables. Furthermore we found a difference in the association
between men and women
The results of this study emphasize the importance of distinguishing between (the
four) different BMI categories when we investigate the nature of the association with
depression. The underweight population should be examined as a distinct category
because there could be a higher level of depression.
For example, in a previous study that focused on the association between obesity
and depression, comparisons of depression levels were made between a sample of
obese and a sample of non-obese subjects which included the underweight sample
[31]. Our findings lead us to conclude that if one compares the levels of depression
between the obese and non obese groups in this way, the results might be less
significant because of the risks of high levels of depression in the underweight group.
According to the DSM-VI, depression is associated with both increased and
decreased food intake, and increased or decreased physical activity [22]. Therefore it
seems logical that increased levels of depression are associated with obesity and
also with underweight.
9
Most studies focus on linear- (positive, negative) or no trends in the association
between obesity and depression. Those studies investigate whether depression
increases or decreases at higher levels of BMI [2].
There are studies that put forward the fact that a subset of the depressed is
actually losing weight as a possible reason why the association between obesity and
depression is not found in many studies [19]. Our study shows that this is indeed a
plausible consideration.
The first strength of our study is that it contains a large sample of participants
(43,534) and a broad variety of socio demographic variables, which we could use as
covariates. The second strength is that the sample is random conducted in the
Netherlands, which makes the results generalizable for the general population.
There were also several limitations. For the assessment of depression symptoms
we used, the MHI. It measures depressive symptoms, but can not be used as a
diagnostic instrument for depression. For the assessment of BMI we used self
reported data. People tend to underestimate there weight and overestimate their
height, this could jeopardize the validity of the results [32, 33]. Like many other
studies concerning the association between BMI and depression, this study is crosssectional. Therefore we can’t explore the onset and causality and the reciprocal
effects in the association between depression and BMI. Longitudinal studies are
needed to examine the course of the depression and possible effect on BMI.
Depression is known to appear in different episodes during a life span, so we need
data on life time prevalence to study the association.
We conclude that our findings clarify the nature of the association between BMI and
depression. We found a U-shaped trend in the association. Longitudinal and
10
experimental studies are needed to explore possible explanations of the relationship
and the direction of causal relationships between BMI and depression.
Competing interests
The authors declare that they have no competing interests
Authors’ contributions
LW wrote the first draft and the revisions of the manuscript. LW and MH conducted
the analyses. AvS, PC and BP critically read each draft and contributed to the further
drafting and revisions of the manuscript.
11
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16
Table 1: Selected characteristics of the sample, and the association with BMI b)
Variable
Value
Gender
Male
Female
20-29
30-39
40-49
50-59
60-69
70+
Preschool only
High school lower level
High school medium level
High school high level
University /college
Dutch
Foreign/western
Foreign /non-western
2001
2002
2003
2004
2005
2006
Age
Education
Ethnicity
Year of survey
Total
No.
21181
22083
6027
8649
8526
7908
5590
5274
6938
6851
3347
15799
9668
37481
3392
2390
6861
6942
6896
7897
7559
7109
Percentage
(%)
48.65
50.72
14.27
20.47
20.18
18.72
13.23
12.48
15.93
15.74
7.69
36.29
22.21
86.66
7.84
5.52
15.86
16.05
15.94
18.25
17.47
16.43
Underweight
(%)
1.11
2.55
4.05
1.72
1.15
0.81
0.91
2.01
1.90
1.72
2.38
2.00
1.46
1.79
2.09
2.47
1.81
2.03
1.97
1.77
1.79
1.74
Normal weight
(%)
47.70
56.86
70.42
56.89
53.00
43.56
39.84
43.08
40.83
46.08
55.46
54.59
60.36
52.29
54.57
50.59
53.29
53.13
51.60
51.64
53.18
51.48
Overweight
(%)
41,7
28.97
20.97
32.18
35.16
41.79
44.35
42.78
40.28
38.50
32.38
34.29
31.71
35.47
33.37
33.64
35.48
35.00
35.77
35.49
34.13
35.39
Obese
(%)
9.49
11.61
4.56
9.21
10.68
13.66
10.82
12.53
16.98
13.69
9.78
9.12
6.46
10.45
9.96
13.31
9.63
9.84
10.66
11.09
10.09
11.38
P
0.000
0.000
0.000
0.000
0.009
ª) All associations were examined with χ² analyses
b)
BMI Categories: Underweight (14-18.5 kg/m2), Normal weight (18.5-25 kg/m2), Overweight (25-30 kg/m2), Obesity (30-60 kg/m2).
17
Table 2: The regression statistics for the U-shaped association
between continuous BMI and depression.
Variable
All
Gender
Age
Value
Male
Female
20-29
30-39
40-49
50-59
60-69
70+
a)
β
0.430
0.381
0.258
0.327
0.530
0.330
0.530
0.577
0.328
Standard Error
0.002
0.004
0.003
0.007
0.005
0.005
0.006
0.008
0.008
P
0.000
0.000
0.000
0.001
0.000
0.000
0.000
0.000
0.001
a)
We report the squared data; a positive value indicates that past a certain point of BMI, the level of
depression increases (U-curve).
18
Figure 1: U-curved association between BMI and Depression
27
25
Depression
23
21
19
17
15
underw eight
normal
overw eight
obese
BMI
Overall
Figure 1
Polynoom (Overall)